Surface enhanced Raman spectroscopy of Chlamydia trachomatis and Neisseria gonorrhoeae for diagnostics, and extra-cellular metabolomics and biochemical monitoring

Metabolite-Mediated Bacterial Antibiotic Resistance Revealed by Surface-Enhanced Raman Spectroscopy

A prompt on-site, real-time method to detect bacterial antibiotic resistance is crucial for controlling the spread of resistance. Herein, we report the use of surface-enhanced Raman spectroscopy (SERS) for the monitoring of bioactive metabolites produced by ampicillin-resistant Pseudomonas aeruginosa strains and identification of mechanisms underlying antibiotic resistance. The results indicate that the blue-green pigment pyocyanin (PYO) dominates the metabolite signals and is significantly enhanced upon exposure to subminimal inhibitory concentrations of ampicillin. PYO accumulates during exponential growth and subsequently either diffuses into the culture medium or is consumed in response to nutrient deprivation. The SERS spectra further reveal that the production of some intermediate substances such as polysaccharides and amino acids is minimally impacted and that nutrient consumption remains consistent. Moreover, the intensity changes and peak shifts observed in the SERS spectra of non-PYO-producing ampicillin-susceptible Escherichia coli demonstrate that exogenously added PYO enhances E. coli tolerance to ampicillin to some extent. These results indicate that PYO mediates antibiotic resistance not only in the parent species but also in cocultured bacterial strains. The metabolic SERS signal provides new insight regarding antibiotic resistance with promising applications for both environmental monitoring and rapid clinical detection.

Ultra-sensitive, rapid detection of dried bloodstains by surface enhanced Raman scattering on Ag substrates

A simple water extraction and transfer procedure is found to result in reproducible and highly sensitive 785 nm excited SERS spectra of 24 h dried bloodstains on Ag nanoparticle substrates. This protocol allows confirmatory detection and identification of dried stains of blood that have been diluted by up to 10⁵ in water on Ag substrates. While previous SERS results demonstrated similar performance on Au substrates when a 50% acetic acid extraction and transfer procedure was used, the water/Ag methodology avoids any potential DNA damage when the sample size is extremely small (≤∼1 μL) due to low pH exposure. The water only procedure is not effective on Au SERS substrates. This metal substrate difference results from the efficient red blood cell lysis and hemoglobin denaturation effects of the Ag nanoparticle surfaces as compare to that of Au nanoparticles. Consequently, the 50% acetic acid exposure is required for the acquisition of 785 nm SERS spectra of dried bloodstains on Au substrates.

Investigation of the Influence of Stress on Label-Free Bacterial Surface-Enhanced Raman Spectra

Label-free surface-enhanced Raman spectroscopy (SERS) has been proposed as a promising bacterial detection technique. However, the quality of the collected bacterial spectra can be affected by the time between sample acquisition and the SERS measurement. This study evaluated how storage stress stimuli influence the label-free SERS spectra of Pseudomonas syringae samples stored in phosphate buffered saline. The results indicate that when faced with nutrient limitations and changes in osmatic pressure, samples at room temperature (25 °C) exhibit more significant spectral changes than those stored at cold temperature (4 °C). At higher temperatures, bacterial communities secrete extracellular biomolecules that induce programmed cell death and result in increases in the supernatant SERS signals. Surviving cells consume cellular components to support their metabolism, thus leading to measurable declines in cell SERS intensity. Two-dimensional correlation spectroscopy analysis suggests that cellular component signatures decline sequentially in the following order: proteins, nucleic acids, and lipids. Extracellular nucleic acids, proteins, and carbohydrates are secreted in turn. After subtracting the SERS changes resulting from storage, we evaluated bacterial response to viral infection. P. syringae SERS profile changes enable accurate bacteriophage Phi6 quantification over the range of 10⁴-10¹⁰ PFU/mL. The results indicate that storage conditions impact bacterial label-free SERS signals and that such influences need to be accounted for and if possible avoided when detecting bacteria or evaluating bacterial response to stress stimuli.

Use of Nanoparticle Decorated Surface-Enhanced Raman Scattering Active Sol-Gel Substrates for SALDI-MS Analysis

Spectroscopy and mass spectrometry techniques are sometimes combined into the same analytical workflow to leverage each technique's analytical benefits. This combined workflow is especially useful in forensic and medical contexts where samples are often precious in nature. Here, we adopt metal nanoparticle (NP) doped sol-gel substrates, initially developed for surface-enhanced Raman scattering (SERS) analysis, as surface-assisted laser desorption/ionization-mass spectrometry (SALDI-MS) substrates. Using dried blood and sample protocols previously developed for SERS analysis, we observe heme-related spectral features on both silver and gold NP substrates by SALDI-MS, demonstrating dual functionality for these orthogonal techniques. Modifying the dried blood extraction procedures also allows for the observation of blood triacylglycerols by SALDI-MS. This is the first demonstration of a SERS/SALDI-MS substrate based on a sol-gel scaffold and the first demonstration of a gold NP sol-gel substrate for SALDI-MS which features lower substrate-related SALDI-MS background compared to the silver substrate.

Label-Free Surface-Enhanced Raman Spectroscopic Analysis of Proteins: Advances and Applications

Surface-enhanced Raman spectroscopy (SERS) is powerful for structural characterization of biomolecules under physiological condition. Owing to its high sensitivity and selectivity, SERS is useful for probing intrinsic structural information of proteins and is attracting increasing attention in biophysics, bioanalytical chemistry, and biomedicine. This review starts with a brief introduction of SERS theories and SERS methodology of protein structural characterization. SERS-active materials, related synthetic approaches, and strategies for protein-material assemblies are outlined and discussed, followed by detailed discussion of SERS spectroscopy of proteins with and without cofactors. Recent applications and advances of protein SERS in biomarker detection, cell analysis, and pathogen discrimination are then highlighted, and the spectral reproducibility and limitations are critically discussed. The review ends with a conclusion and a discussion of current challenges and perspectives of promising directions.

Raman Spectroscopy—A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings

Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful—quick, non-invasive, and non-destructive —tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.

Potential of Mesenchymal Stem Cell-Derived Exosomes as a Novel Treatment for Female Infertility Caused by Bacterial Infections

Neisseria gonorrhoeae and Chlamydia trachomatis are the most common causes of bacterial sexually transmitted diseases (STDs) with complications in women, including pelvic inflammatory disease (PID), ectopic pregnancy, and infertility. The main concern with these infections is that 70% of infected women are asymptomatic and these infections ascend to the upper female reproductive tract (FRT). Primary infection in epithelial cells creates a cascade of events that leads to secretion of pro-inflammatory cytokines that stimulate innate immunity. Production of various cytokines is damaging to mucosal barriers, and tissue destruction leads to ciliated epithelial destruction that is associated with tubal scarring and ultimately provides the conditions for infertility. Mesenchymal stem cells (MSCs) are known as tissue specific stem cells with limited self-renewal capacity and the ability to repair damaged tissues in a variety of pathological conditions due to their multipotential differentiation capacity. Moreover, MSCs secrete exosomes that contain bioactive factors such as proteins, lipids, chemokines, enzymes, cytokines, and immunomodulatory factors which have therapeutic properties to enhance recovery activity and modulate immune responses. Experimental studies have shown that local and systemic treatment of MSC-derived exosomes (MSC-Exos) suppresses the destructive immune response due to the delivery of immunomodulatory proteins. Interestingly, some recent data have indicated that MSC-Exos display strong antimicrobial effects, by the secretion of antimicrobial peptides and proteins (AMPs), and increase bacterial clearance by enhancing the phagocytic activity of host immune cells. Considering MSC-Exos can secrete different bioactive factors that can modulate the immune system and prevent infection, exosome therapy is considered as a new therapeutic method in the treatment of inflammatory and microbial diseases. Here we intend to review the possible application of MSC-Exos in female reproductive system bacterial diseases.

Recent advances in antibiotic resistance diagnosis using SERS: focus on the “Big 5” challenges

SERS for antibiotic resistance diagnosis.

Silver Flowerlike Structures for Surface-Enhanced Raman Spectroscopy

Micro- and nanoflowers are a class of materials composed of particles with high surface-to-volume ratio. They have been extensively studied in the last decade due to simple preparation protocols and promising applications in biosensing, as drug delivery agents, for water purification, and so on. Flowerlike objects, due to their highly irregular surface, may act also as plasmonic materials, providing resonant coupling between optical waves and surface plasmon excitations. This fact allows us to infer the possibility to use micro- and nanoflowers as effective surface-enhanced Raman scattering (SERS) substrate materials. Here, we report on the design and Raman enhancement properties of silver flowerlike structures, deposited on aluminum surface. A simple and cost-effective fabrication method is described, which leads to SERS substrates of high developed surface area. The morphology of the silver flowers on a nanoscale is characterized by self-organized quasiperiodic stacks of nanosheets, which act as plasmonic cavity resonators. The substrates were tested against rhodamine-6G (R6G) water solutions of concentration varying between 10⁻³ M and 10⁻⁷ M. Optimal SERS enhancement factors of up to 10⁵ were established at R6G concentrations in the 10⁻⁶–10⁻⁷ M range.

Surface enhanced Raman scattering specificity for detection and identification of dried bloodstains

Surface enhanced Raman spectroscopy (SERS) provides highly specific vibrational signatures identifying dried blood for a variety of forensic applications. SERS spectra on Au nanoparticle substrates excited at 785 nm are found to identify dried stains of human and nonhuman blood from seven animals, and distinguish stains due to menstrual and peripheral blood. In addition, the unique SERS bloodstain spectrum is distinct from the SERS spectra of thirty red-brown stains of potential household substances that could be visually mistaken for bloodstains and from food stains that have been shown to give positive results with presumptive colorimetric blood tests. Finally, a SERS swab procedure has been developed and demonstrates that the substrates that a blood sample dried on does not offer any Raman or fluorescence interference for the SERS identification of dried blood. Such bloodstains on porous and nonporous materials are all identical and exclusively due to the heme moiety of hemoglobin. Optimized selection of the extraction solvent is found to control the chemical composition of molecular components appearing in the SERS spectrum of complex, multicomponent biological mixtures, such as body fluids.

Analysis of Raman Spectra by Using Deep Learning Methods in the Identification of Marine Pathogens

The need for efficient and accurate identification of pathogens in seafood and the environment has become increasingly urgent, given the current global pandemic. Traditional methods are not only time consuming but also lead to sample wastage. Here, we have proposed two new methods that involve Raman spectroscopy combined with a long short-term memory (LSTM) neural network and compared them with a method using a normal convolutional neural network (CNN). We used eight strains isolated from the marine organism Urechis unicinctus, including four kinds of pathogens. After the models were configured and trained, the LSTM methods that we proposed achieved average isolation-level accuracies exceeding 94%, not only meeting the requirement for identification but also indicating that the proposed methods were faster and more accurate than the normal CNN models. Finally, through a computational approach, we designed a loss function to explore the mechanism reflected by the Raman data, finding the Raman segments that most likely exhibited the characteristics of nucleic acids. These novel experimental results provide insights for developing additional deep learning methods to accurately analyze complex Raman data.

In Search of Spectroscopic Signatures of Periodontitis: A SERS-Based Magnetomicrofluidic Sensor for Detection of Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans

Recently, Porphyromonas gingivalis, the keystone pathogen implicated in the development of gum disease (periodontitis), was detected in the brains of Alzheimer’s disease patients, opening up a fascinating possibility that it is also involved in the pathobiology of this neurodegenerative illness. To verify this hypothesis, an unbiased, specific, and sensitive method to detect this pathogen in biological specimens is needed. To this end, our interdisciplinary studies demonstrate that P. gingivalis can be easily identified by surface-enhanced Raman scattering (SERS). Moreover, based on SERS measurements, P. gingivalis can be distinguished from another common periodontal pathogen, Aggregatibacter actinomycetemcomitans, and also from ubiquitous oral Streptococcus spp. The results were confirmed by principal component analysis (PCA). Furthermore, we have shown that different P. gingivalis and A. actinomycetemcomitans strains can easily adsorb to silver-coated magnetic nanoparticles (Fe₂O₃@AgNPs). Thus, it is possible to magnetically separate investigated bacteria from other components of a specimen using the microfluidic chip. To obtain additional enhancement of the Raman signal, the NPs adsorbed to bacterial cells were magnetically attracted to the Si/Ag SERS platform. Afterward, the SERS spectra could be recorded. Such a time-saving procedure can be very helpful in rapid medical diagnostics and thus in starting the appropriate pharmacological therapy to prevent the development of periodontitis and associated comorbidities, e.g., Alzheimerʼs disease.

Preparation of Hydrophobic Film by Electrospinning for Rapid SERS Detection of Trace Triazophos

For real application, it is an urgent demand to fabricate stable and flexible surface-enhanced Raman scattering (SERS) substrates with high enhancement factors in a large-scale and facile way. Herein, by using the electrospinning technique, a hydrophobic and flexible poly(styrene-co-butadiene) (SB) fibrous membrane is obtained, which is beneficial for modification of silver nanoparticles (Ag NPs) colloid in a small region and then formation of more "hot spots" by drying; the final SERS substrate is designated as Ag/SB. Hydrophobic Ag/SB can efficiently capture heterocyclic molecules into the vicinity of hot spots of Ag NPs. Such Ag/SB films are used to quantitatively detect trace triazophos residue on fruit peels or in the juice, and the limit of detection (LOD) of 2.5 × 10^-8 M is achieved. Ag/SB films possess a capability to resist heat. As a case, 6-mercaptopurine (6MP) that just barely dissolves in 90 °C water is picked for conducting Ag/SB-film-based experiments.

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.

Plasmon-enhanced stimulated Raman scattering microscopy with single-molecule detection sensitivity

Stimulated Raman scattering (SRS) microscopy allows for high-speed label-free chemical imaging of biomedical systems. The imaging sensitivity of SRS microscopy is limited to ~10 mM for endogenous biomolecules. Electronic pre-resonant SRS allows detection of sub-micromolar chromophores. However, label-free SRS detection of single biomolecules having extremely small Raman cross-sections (~10^-30 cm² sr^-1) remains unreachable. Here, we demonstrate plasmon-enhanced stimulated Raman scattering (PESRS) microscopy with single-molecule detection sensitivity. Incorporating pico-Joule laser excitation, background subtraction, and a denoising algorithm, we obtain robust single-pixel SRS spectra exhibiting single-molecule events, verified by using two isotopologues of adenine and further confirmed by digital blinking and bleaching in the temporal domain. To demonstrate the capability of PESRS for biological applications, we utilize PESRS to map adenine released from bacteria due to starvation stress. PESRS microscopy holds the promise for ultrasensitive detection and rapid mapping of molecular events in chemical and biomedical systems.

Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning

Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from bacterial cells and numerous bacterial species and phenotypes. Here we generate an extensive dataset of bacterial Raman spectra and apply deep learning approaches to accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve average isolate-level accuracies exceeding 82% and antibiotic treatment identification accuracies of 97.0±0.3%. We also show that this approach distinguishes between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89±0.1% accuracy. We validate our results on clinical isolates from 50 patients. Using just 10 bacterial spectra from each patient isolate, we achieve treatment identification accuracies of 99.7%. Our approach has potential for culture-free pathogen identification and antibiotic susceptibility testing, and could be readily extended for diagnostics on blood, urine, and sputum.

The use of Raman spectroscopy for pathogen identification is hampered by the weak Raman signal and phenotypic diversity of bacterial cells. Here the authors generate an extensive dataset of bacterial Raman spectra and apply deep learning to identify common bacterial pathogens and predict antibiotic treatment from noisy Raman spectra.

"Three-in-One" SERS Adhesive Tape for Rapid Sampling, Release, and Detection of Wound Infectious Pathogens

The traditional colony culture method for detection of pathogens is subjected to the laborious and tedious experimental procedure, which limits its application in point-of-care (POC) testing and quick diagnosis. This work designs an intelligent adhesive tape as a "three-in-one" platform for rapid sampling, photocontrolled release, and surface-enhanced Raman scattering (SERS) detection of pathogens from infected wounds. This tape is constructed by encapsulating densely packed gold nanostars as SERS substrates between two pieces of graphene and modified with a synthetic o-nitrobenzyl derivative molecule to form an artificial biointerface for highly efficient pathogen capture via electrostatic interaction. The captured targets can be conveniently released onto a solid culture medium by UV cleavage of o-nitrobenzyl moiety for pathogen growth and in situ SERS detection. As a proof of strategy, this "three-in-one" platform has been used for detecting the concurrent infection of Pseudomonas aeruginosa and Staphylococcus aureus by pasting the tape on a skin burn wound. The impressive detection performance with an analytical time of only several hours for these pathogens at an early growth stage demonstrates its great potential as a POC testing device for health care.

Assembly of gold nanoparticles using turnip yellow mosaic virus as an in-solution SERS sensor

A common challenge in nanotechnology is the conception of materials with well-defined nanoscale structure. In recent years, virus capsids have been used as templates to create a network to organize 3D nano-objects, building thus new functional nanomaterials and then devices. In this work, we synthetized 3D gold nanoclusters and we used them as Surface Enhanced Raman Scattering (SERS) sensor substrates in solution. In practice, gold nanoparticles (AuNPs) were grafted on turnip yellow mosaic virus (TYMV) capsid, an icosahedral plant virus. Two strategies were considered to covalently bind AuNPs of different sizes (5, 10 and 20 nm) to TYMV. After purification by agarose electrophoresis and digestion by agarase, the resulting nano-bio-hybrid AuNP-TYVM was characterized by different tools. Typically, dynamic light scattering (DLS) confirmed the grafting through the hydrodynamic size increase by comparing AuNPs alone to AuNP-TYMV (up to 33, 50 and 68 nm for 5, 10 and 20 nm sized AuNPs, respectively) or capsids alone (28 nm). Transmission electronic microscopy (TEM) observations revealed that AuNPs were arranged with 5-fold symmetry, in agreement with their grafting around icosahedral capsids. Moreover, UV-vis absorption spectroscopy showed a red-shift of the plasmon absorption band on the grafted AuNP spectrum (530 nm) compared to that of the non-grafted one (520 nm). Finally, by recording in solution the Raman spectra of a dissolved probe molecule, namely 1,2-bis(4-pyridyl)ethane (BPE), in the presence of AuNP-TYVM and bare AuNPs or capsids, a net enhancement of the Raman signal was observed when BPE is adsorbed on AuNP-TYVM. The analytical enhancement factor (AEF) value of AuNP-TYMV is 5 times higher than that of AuNPs. These results revealed that AuNPs organized around virus capsid are able to serve as in-solution SERS-substrates, which is very interesting for the conception of ultrasensitive sensors in biological media.

3D-assembly of gold nanoparticles onto turnip yellow mosaic virus.

Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) has recently gained increasing attention for the detection of trace quantities of biomolecules due to its excellent molecular specificity, ultrasensitivity, and quantitative multiplex ability. Specific single or multiple biomarkers in complex biological environments generate strong and distinct SERS spectral signals when they are in the vicinity of optically active nanoparticles (NPs). When multivariate chemometrics are applied to decipher underlying biomarker patterns, SERS provides qualitative and quantitative information on the inherent biochemical composition and properties that may be indicative of healthy or diseased states. Moreover, SERS allows for differentiation among many closely-related causative agents of diseases exhibiting similar symptoms to guide early prescription of appropriate, targeted and individualised therapeutics. This review provides an overview of recent progress made by the application of SERS in the diagnosis of cancers, microbial and respiratory infections. It is envisaged that recent technology development will help realise full benefits of SERS to gain deeper insights into the pathological pathways for various diseases at the molecular level.

Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy

(1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA.